It's probably worth mentioning that there are a lot of ways to implement convolution with a kernel, and the kernel can be of any size, not just 3×3. The explanation here shows how to implement the output-side algorithm nonrecursively; http://www.dspguide.com/ch6/3.htm gives this for the one-dimensional case. But you can implement it on the input side instead (iterating over the input samples instead of the output samples), there are kernels that have a much more efficient recursive implementation (including zero-phase kernels using time-reversal), you can implement very large kernels if you can afford to do the convolution in the frequency domain, and there's a whole class of kernels that have efficient sparse filter cascade representations, including large Gaussians.

(To say nothing of convolutions over other rings.)